Global Wheat Head Detection Challenges: Winning Models and Application for Head Counting

Data competitions have become a popular approach to crowdsource new data analysis methods for general and specialized data science problems. Data competitions have a rich history in plant phenotyping, and new outdoor field datasets have the potential to embrace solutions across research and commerci...

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Bibliographic Details
Published in:Plant phenomics 2023-01, Vol.5, p.0059-0059, Article 0059
Main Authors: David, Etienne, Ogidi, Franklin, Smith, Daniel, Chapman, Scott, de Solan, Benoit, Guo, Wei, Baret, Frederic, Stavness, Ian
Format: Article
Language:English
Subjects:
Environmental Sciences
Life Sciences
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Summary:Data competitions have become a popular approach to crowdsource new data analysis methods for general and specialized data science problems. Data competitions have a rich history in plant phenotyping, and new outdoor field datasets have the potential to embrace solutions across research and commercial applications. We developed the Global Wheat Challenge as a generalization competition in 2020 and 2021 to find more robust solutions for wheat head detection using field images from different regions. We analyze the winning challenge solutions in terms of their robustness when applied to new datasets. We found that the design of the competition had an influence on the selection of winning solutions and provide recommendations for future competitions to encourage the selection of more robust solutions.
ISSN:2643-6515
2643-6515
DOI:10.34133/plantphenomics.0059